- Table View
- List View
Data Protection for Photographers
by Patrick H. CorriganAll photographers, both amateur and professional, are faced with the important issues of data protection and storage. Without knowledge of the options, tools, and procedures for safe and effective image protection and storage, photographers run the serious risk of losing their image files. This book offers critical information about the best hardware, software, procedures, and practices for capturing, storing, and preserving images and other data. This book explains current data protection and storage technologies in everyday terms. It describes effective procedures for protecting data, from capture to backup and archiving. Descriptions of specific products applicable to Windows, MacOS, and Linux systems are provided.
Data Science and Artificial Intelligence: First International Conference, DSAI 2023, Bangkok, Thailand, November 27–29, 2023, Proceedings (Communications in Computer and Information Science #1942)
by Marcello M. Bonsangue Chutiporn AnutariyaThis book constitutes the proceedings of the First International Conference, DSAI 2023, held in Bangkok, Thailand, during November 27–30, 2023. The 22 full papers and the 4 short papers included in this volume were carefully reviewed and selected from 70 submissions. This volume focuses on ideas, methodologies, and cutting-edge research that can drive progress and foster interdisciplinary collaboration in the fields of data science and artificial intelligence.
Data Science and Emerging Technologies: Proceedings of DaSET 2022 (Lecture Notes on Data Engineering and Communications Technologies #165)
by Michael W. Berry Dhiya Al-Jumeily Azlinah Mohamed Yap Bee WahThe book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning.
Data Science and Visual Computing (Advanced Information and Knowledge Processing)
by Rae Earnshaw David Kasik John DillData science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities. The range and volume of data sources has increased enormously over time, particularly those generating real-time data. This has posed additional challenges for data management and data analysis of the data and effective representation and display. A wide range of application areas are able to benefit from the latest visual tools and facilities. Rapid analysis is needed in areas where immediate decisions need to be made. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze all of it, attention is being focussed how best to address these challenges. Optimum ways of addressing large data sets across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. Being driven by national priority, they are able to attract support for research and development within their organizations and institutions to bring together interdisciplinary expertise to address a wide variety of problems. Visual computing is a set of tools and methodologies that utilize 2D and 3D images to extract information from data. Such methods include data analysis, simulation, and interactive exploration. These are analyzed and discussed.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part I (Communications in Computer and Information Science #1058)
by Weipeng Jing Xianhua Song Zeguang Lu Xiaohui ChengThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part II (Communications in Computer and Information Science #1059)
by Hongzhi Wang Zeguang Lu Xiaolan Xie Rui MaoThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17–20, 2021, Proceedings, Part I (Communications in Computer and Information Science #1451)
by Weipeng Jing Xianhua Song Zeguang Lu Pinle Qin Jianchao ZengThis two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
Data Sketches: A journey of imagination, exploration, and beautiful data visualizations (AK Peters Visualization Series)
by Nadieh Bremer Shirley WuIn Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right. This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges overcome during each project Full-color pages, showcasing all 24 final data visualizations This book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.
Data Storytelling and Visualization with Tableau: A Hands-on Approach
by Parikshit Narendra Mahalle Prachi Manoj JoshiWith the tremendous growth and availability of the data, this book covers understanding the data, while telling a story with visualization including basic concepts about the data, the relationship and the visualizations. All the technical details that include installation and building the different visualizations are explained in a clear and systematic way. Various aspects pertaining to storytelling and visualization are explained in the book through Tableau. Features Provides a hands-on approach in Tableau in a simplified manner with steps Discusses the broad background of data and its fundamentals, from the Internet of Everything to analytics Emphasizes the use of context in delivering the stories Presents case studies with the building of a dashboard Presents application areas and case studies with identification of the impactful visualization This book will be helpful for professionals, graduate students and senior undergraduate students in Manufacturing Engineering, Civil and Mechanical Engineering, Data Analytics and Data Visualization.
Data Visualization Made Simple: Insights into Becoming Visual
by Kristen SosulskiData Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more. In nine appealing chapters, the book: examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research; scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems.
Data Visualization for Design Thinking: Applied Mapping
by Winifred E. NewmanData Visualization for Design Thinking helps you make better maps. Treating maps as applied research, you’ll be able to understand how to map sites, places, ideas, and projects, revealing the complex relationships between what you represent, your thinking, the technology you use, the culture you belong to, and your aesthetic practices. More than 100 examples illustrated with over 200 color images show you how to visualize data through mapping. Includes five in-depth cases studies and numerous examples throughout.
Data Visualization for People of All Ages (ISSN)
by Nancy OrganData visualization is the art and science of making information visible. On paper and in our imaginations, it’s a language of shapes and colors that holds our best ideas and most important questions. As we find ourselves swimming in data of all kinds, visualization can help us to understand, express, and explore the richness of the world around us. No matter your age or background, this book opens the door to new ways of thinking and sharing through the power of data visualization.Data Visualization for People of All Ages is a field guide to visual literacy, born from the author’s personal experience working with world-class scholars, engineers, and scientists. By walking through the different ways of showing data—including color, angle, position, and length—you’ll learn how charts and graphs truly work so that no visualization is ever a mystery or out of reach. It doesn’t stop at what fits on a page, either. You’ll journey into cutting-edge topics like data sonification and data physicalization, using sound and touch to share data across the different senses. Packed with practical examples and exercises to help you connect the dots, this book will teach you how to create and understand data visualizations on your own—all without writing a single line of code or getting tangled up in software.Written with accessibility in mind, this book invites everyone to the table to share the joy of one of today’s most necessary skills. Perfect for home or classroom use, this friendly companion gives people of all ages everything they need to start visualizing with confidence.
Data Visualization in Excel: A Guide for Beginners, Intermediates, and Wonks (AK Peters Visualization Series)
by Jonathan SchwabishThis book closes the gap between what people think Excel can do and what they can achieve in the tool. Over the past few years, recognition of the importance of effectively visualizing data has led to an explosion of data analysis and visualization software tools. But for many people, Microsoft Excel continues to be the workhorse for their data visualization needs, not to mention the only tool that many data workers have access to. Although Excel is not a specialist data visualization platform, it does have strong capabilities. The default chart types do not need to be the limit of the tool’s data visualization capabilities, and users can extend its features by understanding some key elements and strategies. Data Visualization in Excel provides a step-by-step guide to creating more advanced and often more effective data visualizations in Excel and is the perfect guide for anyone who wants to create better, more effective, and more engaging data visualizations.
Data Visualization: Charts, Maps, and Interactive Graphics (ASA-CRC Series on Statistical Reasoning in Science and Society)
by Robert GrantThis is the age of data. There are more innovations and more opportunities for interesting work with data than ever before, but there is also an overwhelming amount of quantitative information being published every day. Data visualisation has become big business, because communication is the difference between success and failure, no matter how clever the analysis may have been. The ability to visualize data is now a skill in demand across business, government, NGOs and academia. Data Visualization: Charts, Maps, and Interactive Graphics gives an overview of a wide range of techniques and challenges, while staying accessible to anyone interested in working with and understanding data. Features: Focusses on concepts and ways of thinking about data rather than algebra or computer code. Features 17 short chapters that can be read in one sitting. Includes chapters on big data, statistical and machine learning models, visual perception, high-dimensional data, and maps and geographic data. Contains more than 125 visualizations, most created by the author. Supported by a website with all code for creating the visualizations, further reading, datasets and practical advice on crafting the images. Whether you are a student considering a career in data science, an analyst who wants to learn more about visualization, or the manager of a team working with data, this book will introduce you to a broad range of data visualization methods. Cover image: Landscape of Change uses data about sea level rise, glacier volume decline, increasing global temperatures, and the increasing use of fossil fuels. These data lines compose a landscape shaped by the changing climate, a world in which we are now living. Copyright © Jill Pelto (jillpelto.com).
Data Visualization: Principles and Practice, Second Edition
by Alexandru C. TeleaDesigning a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration wi
Data Visualization: Representing Information on Modern Web
by Swizec Teller Simon Timms Andy Kirk Ændrew RininslandUnleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book * Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success * Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options * A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn * Harness the power of D3 by building interactive and real-time data-driven web visualizations * Find out how to use JavaScript to create compelling visualizations of social data * Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution * Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics * Explore the various features of HTML5 to design creative visualizations * Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ * Gain a solid understanding of the common D3 development idioms * Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. In third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: ? Data Visualization: a successful design process by Andy Kirk ? Social Data Visualization with HTML5 and JavaScript by Simon Timms ? Learning d3.js Data Visualization, Second Edition by Ændrew Rininsland and Swizec Teller Style and approach This course includes all the resources that will help you jump into creating interactive and engaging visualizations for the web. Through this comprehensive course, you'll learn how to create engaging visualizations for the web to represent your data from start to finish!
Data Visualization: a successful design process
by Andy KirkA comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
Data Wrangling with R
by Bradley C. BoehmkeThis guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets
Data, Architecture and the Experience of Place
by Anastasia KarandinouThe notion of data is increasingly encountered in spatial, creative and cultural studies. Big data and artificial intelligence are significantly influencing a number of disciplines. Processes, methods and vocabularies from sciences, architecture, arts are borrowed, discussed and tweaked, and new cross-disciplinary fields emerge. More and more, artists and designers are drawing on hard data to interpret the world and to create meaningful, sensuous environments. Architects are using neurophysiological data to improve their understanding of people’s experiences in built spaces. Different disciplines collaborate with scientists to visualise data in different and creative ways, revealing new connections, interpretations and readings. This often demonstrates a genuine desire to comprehend human behaviour and experience and to – possibly – inform design processes accordingly. At the same time, this opens up questions as to why this desire and curiosity is emerging now, how it relates to recent technological advances and how it converses with the cultural, philosophical and methodological context of the disciplines with which it engages. Questions are also raised as to how the use of data and data-informed methods may serve, support, promote and/or challenge political agendas. Data, Architecture and the Experience of Place provides an overview of new approaches on this significant subject and is ideal for students and researchers in digital architecture, architectural theory, design, digital media, sensory studies and related fields.
Data, Matter, Design: Strategies in Computational Design
by Frank MelendezData, Matter, Design presents a comprehensive overview of current design processes that rely on the input of data and use of computational design strategies, and their relationship to an array of outputs. Technological changes, through the use of computational tools and processes, have radically altered and influenced our relationship to cities and the methods by which we design architecture, urban, and landscape systems. This book presents a wide range of curated projects and contributed texts by leading architects, urbanists, and designers that transform data as an abstraction, into spatial, experiential, and performative configurations within urban ecologies, emerging materials, robotic agents, adaptive fields, and virtual constructs. Richly illustrated with over 200 images, Data, Matter, Design is an essential read for students, academics, and professionals to evaluate and discuss how data in design methodologies and theoretical discourses have evolved in the last two decades and why processes of data collection, measurement, quantification, simulation, algorithmic control, and their integration into methods of reading and producing spatial conditions, are becoming vital in academic and industry practices.
Data-Driven Decision Making for Product Service Systems
by Xavier Boucher Giuditta Pezzotta Roberto Sala Marco Bertoni Fabiana PirolaThis book is a compilation of theoretical and practical contributions aimed at facilitating the servitization of manufacturing companies, specifically focusing on data-driven decision-making within the context of Product-Service Systems (PSS). Providing a comprehensive overview, it discusses the latest breakthroughs in operational, tactical, and strategic decision-making for PSS, leveraging data-driven processes, methodologies, and tools. Therefore, the book significantly contributes to strengthening the knowledge on the use of data-driven decision-making methods and tools all the phases of the PSS lifecycle.From extended warranties and leasing to pay-per-use and other innovative configurations, manufacturing companies are increasingly adopting servitized business models and PSS to create additional value for their customers and users and create robust relationships with them, ensuring more reliable cash flows. In this setting, effective information management and the utilization of aggregated operational data have become essential for guiding strategic, tactical, and operational decisions.This book not only consolidates theoretical frameworks but also offers practical insights into data-driven decision-making in PSS, providing deep knowledge on how complex decisions can be taken along the various phases of the PSS lifecycle using data-driven methods and tools. Key areas of focus include: 1. In the Beginning of Life, introducing new services tailored to customer needs, disclosing new business opportunities in terms of revenues, and extending the PSS Middle of Life.2. Designing or re-designing assets and/or services, thereby influencing the PSS Beginning of Life.3. Enhancing daily decisions related to asset management to improve the PSS Middle of Life.4. Optimizing daily decisions related to service delivery and management, aimed at enhancing the PSS Middle of Life.5. Facilitating informed decisions on recycling, remanufacturing, refurbishing, and revamping, impacting the PSS End of Life.This book will be of interest to researchers and managers in industry as it offers insights that bridge the gap between theory and practical application in the evolving landscape of PSS.
Data-Driven Design and Construction
by Randy Deutsch"In this comprehensive book, Professor Randy Deutsch has unlocked and laid bare the twenty-first century codice nascosto of architecture. It is data. Big data. Data as driver. . . This book offers us the chance to become informed and knowledgeable pursuers of data and the opportunities it offers to making architecture a wonderful, useful, and smart art form. " --From the Foreword by James Timberlake, FAIA Written for architects, engineers, contractors, owners, and educators, and based on today's technology and practices, Data-Driven Design and Construction: 25 Strategies for Capturing, Applying and Analyzing Building Data addresses how innovative individuals and firms are using data to remain competitive while advancing their practices. seeks to address and rectify a gap in our learning, by explaining to architects, engineers, contractors and owners--and students of these fields--how to acquire and use data to make more informed decisions. documents how data-driven design is the new frontier of the convergence between BIM and architectural computational analyses and associated tools. is a book of adaptable strategies you and your organization can apply today to make the most of the data you have at your fingertips. Data-Driven Design and Construction was written to help design practitioners and their project teams make better use of BIM, and leverage data throughout the building lifecycle.
Data-Driven Modelling of Non-Domestic Buildings Energy Performance: Supporting Building Retrofit Planning (Green Energy and Technology)
by Saleh Seyedzadeh Farzad Pour RahimianThis book outlines the data-driven modelling of building energy performance to support retrofit decision-making. It explains how to determine the appropriate machine learning (ML) model, explores the selection and expansion of a reasonable dataset and discusses the extraction of relevant features and maximisation of model accuracy. This book develops a framework for the quick selection of a ML model based on the data and application. It also proposes a method for optimising ML models for forecasting buildings energy loads by employing multi-objective optimisation with evolutionary algorithms. The book then develops an energy performance prediction model for non-domestic buildings using ML techniques, as well as utilising a case study to lay out the process of model development. Finally, the book outlines a framework to choose suitable artificial intelligence methods for modelling building energy performances. This book is of use to both academics and practising energy engineers, as it provides theoretical and practical advice relating to data-driven modelling for energy retrofitting of non-domestic buildings.
Data-Driven Smart Community Design: Strategies for Fostering Inclusive and Resilient Neighbourhoods
by Keng Hua ChongThis book couples data analytics with social behavioural studies and participatory design to derive deeper insights on city dwellers’ present needs and future aspirations, thereby enabling the development of targeted spatial and programmatic interventions for diverse communities.Public housing in Singapore has been regarded internationally as a success story. This book outlines the latest strategies and concepts for addressing the emerging social challenges of the ageing population: shrinking household size, increasingly diverse demographics and widening inequality, and fostering inclusive and resilient neighbourhoods. Adopting an interdisciplinary approach, this book: Outlines an innovative data-driven planning process for housing neighbourhood and community design Provides a framework for planners and designers to synthesise qualitative and quantitative data analyses Presents a comprehensive set of tested urban analytics tools, digital platforms and participatory toolkits used to design and develop community initiatives. A recommended text for students undertaking urban planning, urban design, housing design, architecture, real estate, urban sociology and community design, the book’s strategies for evidence-based neighbourhood designs will also appeal to practitioners and policymakers.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.
Data-Driven Storytelling (AK Peters Visualization Series)
by Nathalie Henry Riche Christophe Hurter Nicholas Diakopoulos Sheelagh CarpendaleThis book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.